Overview

Brought to you by YData

Dataset statistics

Number of variables9
Number of observations20640
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory72.0 B

Variable types

Numeric9

Alerts

AveRooms is highly overall correlated with MedIncHigh correlation
Latitude is highly overall correlated with LongitudeHigh correlation
Longitude is highly overall correlated with LatitudeHigh correlation
MedHouseVal is highly overall correlated with MedIncHigh correlation
MedInc is highly overall correlated with AveRooms and 1 other fieldsHigh correlation
AveRooms is highly skewed (γ1 = 20.69786896)Skewed
AveBedrms is highly skewed (γ1 = 31.31695625)Skewed
AveOccup is highly skewed (γ1 = 97.63956096)Skewed

Reproduction

Analysis started2024-09-22 12:24:27.013793
Analysis finished2024-09-22 12:24:38.391700
Duration11.38 seconds
Software versionydata-profiling vv4.10.0
Download configurationconfig.json

Variables

MedInc
Real number (ℝ)

HIGH CORRELATION 

Distinct12928
Distinct (%)62.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.870671
Minimum0.4999
Maximum15.0001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size161.4 KiB
2024-09-22T17:54:38.613602image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.4999
5-th percentile1.60057
Q12.5634
median3.5348
Q34.74325
95-th percentile7.300305
Maximum15.0001
Range14.5002
Interquartile range (IQR)2.17985

Descriptive statistics

Standard deviation1.8998217
Coefficient of variation (CV)0.4908249
Kurtosis4.9525241
Mean3.870671
Median Absolute Deviation (MAD)1.0642
Skewness1.6466567
Sum79890.649
Variance3.6093226
MonotonicityNot monotonic
2024-09-22T17:54:38.834643image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.125 49
 
0.2%
15.0001 49
 
0.2%
2.875 46
 
0.2%
2.625 44
 
0.2%
4.125 44
 
0.2%
3.875 41
 
0.2%
3.375 38
 
0.2%
3 38
 
0.2%
4 37
 
0.2%
3.625 37
 
0.2%
Other values (12918) 20217
98.0%
ValueCountFrequency (%)
0.4999 12
0.1%
0.536 10
< 0.1%
0.5495 1
 
< 0.1%
0.6433 1
 
< 0.1%
0.6775 1
 
< 0.1%
0.6825 1
 
< 0.1%
0.6831 1
 
< 0.1%
0.696 1
 
< 0.1%
0.6991 1
 
< 0.1%
0.7007 1
 
< 0.1%
ValueCountFrequency (%)
15.0001 49
0.2%
15 2
 
< 0.1%
14.9009 1
 
< 0.1%
14.5833 1
 
< 0.1%
14.4219 1
 
< 0.1%
14.4113 1
 
< 0.1%
14.2959 1
 
< 0.1%
14.2867 1
 
< 0.1%
13.947 1
 
< 0.1%
13.8556 1
 
< 0.1%

HouseAge
Real number (ℝ)

Distinct52
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.639486
Minimum1
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size161.4 KiB
2024-09-22T17:54:39.023285image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q118
median29
Q337
95-th percentile52
Maximum52
Range51
Interquartile range (IQR)19

Descriptive statistics

Standard deviation12.585558
Coefficient of variation (CV)0.43944774
Kurtosis-0.80062885
Mean28.639486
Median Absolute Deviation (MAD)10
Skewness0.060330638
Sum591119
Variance158.39626
MonotonicityNot monotonic
2024-09-22T17:54:39.217835image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
52 1273
 
6.2%
36 862
 
4.2%
35 824
 
4.0%
16 771
 
3.7%
17 698
 
3.4%
34 689
 
3.3%
26 619
 
3.0%
33 615
 
3.0%
18 570
 
2.8%
25 566
 
2.7%
Other values (42) 13153
63.7%
ValueCountFrequency (%)
1 4
 
< 0.1%
2 58
 
0.3%
3 62
 
0.3%
4 191
0.9%
5 244
1.2%
6 160
0.8%
7 175
0.8%
8 206
1.0%
9 205
1.0%
10 264
1.3%
ValueCountFrequency (%)
52 1273
6.2%
51 48
 
0.2%
50 136
 
0.7%
49 134
 
0.6%
48 177
 
0.9%
47 198
 
1.0%
46 245
 
1.2%
45 294
 
1.4%
44 356
 
1.7%
43 353
 
1.7%

AveRooms
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct19392
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4289997
Minimum0.84615385
Maximum141.90909
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size161.4 KiB
2024-09-22T17:54:39.395252image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.84615385
5-th percentile3.43233
Q14.4407162
median5.2291288
Q36.052381
95-th percentile7.6402465
Maximum141.90909
Range141.06294
Interquartile range (IQR)1.6116647

Descriptive statistics

Standard deviation2.4741731
Coefficient of variation (CV)0.45573278
Kurtosis879.35326
Mean5.4289997
Median Absolute Deviation (MAD)0.80292061
Skewness20.697869
Sum112054.55
Variance6.1215327
MonotonicityNot monotonic
2024-09-22T17:54:39.589801image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 27
 
0.1%
4.5 22
 
0.1%
4 21
 
0.1%
6 20
 
0.1%
5.333333333 13
 
0.1%
5.5 11
 
0.1%
4.666666667 9
 
< 0.1%
5.666666667 8
 
< 0.1%
3 8
 
< 0.1%
7 7
 
< 0.1%
Other values (19382) 20494
99.3%
ValueCountFrequency (%)
0.8461538462 1
< 0.1%
0.8888888889 1
< 0.1%
1 1
< 0.1%
1.130434783 2
< 0.1%
1.260869565 1
< 0.1%
1.378486056 1
< 0.1%
1.411290323 1
< 0.1%
1.465753425 1
< 0.1%
1.550408719 1
< 0.1%
1.553030303 1
< 0.1%
ValueCountFrequency (%)
141.9090909 1
< 0.1%
132.5333333 1
< 0.1%
62.42222222 1
< 0.1%
61.8125 1
< 0.1%
59.875 1
< 0.1%
56.26923077 1
< 0.1%
52.84821429 1
< 0.1%
52.69047619 1
< 0.1%
50.83783784 1
< 0.1%
47.51515152 1
< 0.1%

AveBedrms
Real number (ℝ)

SKEWED 

Distinct14233
Distinct (%)69.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.0966751
Minimum0.33333333
Maximum34.066667
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size161.4 KiB
2024-09-22T17:54:39.765734image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.33333333
5-th percentile0.93910878
Q11.006079
median1.0487805
Q31.0995261
95-th percentile1.2730057
Maximum34.066667
Range33.733333
Interquartile range (IQR)0.09344702

Descriptive statistics

Standard deviation0.47391086
Coefficient of variation (CV)0.43213422
Kurtosis1636.712
Mean1.0966751
Median Absolute Deviation (MAD)0.046086874
Skewness31.316956
Sum22635.375
Variance0.2245915
MonotonicityNot monotonic
2024-09-22T17:54:39.963157image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 288
 
1.4%
1.125 29
 
0.1%
1.058823529 26
 
0.1%
1.1 25
 
0.1%
1.083333333 25
 
0.1%
1.052631579 23
 
0.1%
1.05 21
 
0.1%
1.090909091 21
 
0.1%
1.055555556 20
 
0.1%
1.076923077 18
 
0.1%
Other values (14223) 20144
97.6%
ValueCountFrequency (%)
0.3333333333 1
 
< 0.1%
0.375 1
 
< 0.1%
0.4444444444 1
 
< 0.1%
0.5 3
< 0.1%
0.5263157895 1
 
< 0.1%
0.53125 1
 
< 0.1%
0.5454545455 1
 
< 0.1%
0.5555555556 1
 
< 0.1%
0.5625 2
< 0.1%
0.5714285714 2
< 0.1%
ValueCountFrequency (%)
34.06666667 1
< 0.1%
25.63636364 1
< 0.1%
15.3125 1
< 0.1%
14.11111111 1
< 0.1%
11.41071429 1
< 0.1%
11.18181818 1
< 0.1%
11 1
< 0.1%
10.27027027 1
< 0.1%
10.15384615 1
< 0.1%
9.703703704 1
< 0.1%

Population
Real number (ℝ)

Distinct3888
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1425.4767
Minimum3
Maximum35682
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size161.4 KiB
2024-09-22T17:54:40.153579image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile348
Q1787
median1166
Q31725
95-th percentile3288
Maximum35682
Range35679
Interquartile range (IQR)938

Descriptive statistics

Standard deviation1132.4621
Coefficient of variation (CV)0.79444447
Kurtosis73.553116
Mean1425.4767
Median Absolute Deviation (MAD)440
Skewness4.9358582
Sum29421840
Variance1282470.5
MonotonicityNot monotonic
2024-09-22T17:54:40.373288image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
891 25
 
0.1%
761 24
 
0.1%
1227 24
 
0.1%
1052 24
 
0.1%
850 24
 
0.1%
825 23
 
0.1%
782 22
 
0.1%
999 22
 
0.1%
1005 22
 
0.1%
753 21
 
0.1%
Other values (3878) 20409
98.9%
ValueCountFrequency (%)
3 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
8 4
< 0.1%
9 2
< 0.1%
11 1
 
< 0.1%
13 4
< 0.1%
14 3
< 0.1%
15 2
< 0.1%
17 2
< 0.1%
ValueCountFrequency (%)
35682 1
< 0.1%
28566 1
< 0.1%
16305 1
< 0.1%
16122 1
< 0.1%
15507 1
< 0.1%
15037 1
< 0.1%
13251 1
< 0.1%
12873 1
< 0.1%
12427 1
< 0.1%
12203 1
< 0.1%

AveOccup
Real number (ℝ)

SKEWED 

Distinct18841
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0706552
Minimum0.69230769
Maximum1243.3333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size161.4 KiB
2024-09-22T17:54:40.562301image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.69230769
5-th percentile1.8725448
Q12.4297411
median2.8181157
Q33.2822609
95-th percentile4.3334167
Maximum1243.3333
Range1242.641
Interquartile range (IQR)0.85251978

Descriptive statistics

Standard deviation10.38605
Coefficient of variation (CV)3.3823562
Kurtosis10651.011
Mean3.0706552
Median Absolute Deviation (MAD)0.41952559
Skewness97.639561
Sum63378.322
Variance107.87003
MonotonicityNot monotonic
2024-09-22T17:54:40.745679image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3 35
 
0.2%
2 18
 
0.1%
2.5 17
 
0.1%
2.666666667 16
 
0.1%
2.333333333 13
 
0.1%
2.6 12
 
0.1%
3.2 11
 
0.1%
2.555555556 10
 
< 0.1%
4 9
 
< 0.1%
2.764705882 9
 
< 0.1%
Other values (18831) 20490
99.3%
ValueCountFrequency (%)
0.6923076923 1
< 0.1%
0.75 1
< 0.1%
0.9705882353 1
< 0.1%
1.060606061 1
< 0.1%
1.066176471 1
< 0.1%
1.089267803 1
< 0.1%
1.089285714 1
< 0.1%
1.161290323 1
< 0.1%
1.169329073 1
< 0.1%
1.215873016 1
< 0.1%
ValueCountFrequency (%)
1243.333333 1
< 0.1%
599.7142857 1
< 0.1%
502.4615385 1
< 0.1%
230.1724138 1
< 0.1%
83.17142857 1
< 0.1%
63.75 1
< 0.1%
51.4 1
< 0.1%
41.21428571 1
< 0.1%
33.95294118 1
< 0.1%
21.33333333 1
< 0.1%

Latitude
Real number (ℝ)

HIGH CORRELATION 

Distinct862
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.631861
Minimum32.54
Maximum41.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size161.4 KiB
2024-09-22T17:54:40.934121image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum32.54
5-th percentile32.82
Q133.93
median34.26
Q337.71
95-th percentile38.96
Maximum41.95
Range9.41
Interquartile range (IQR)3.78

Descriptive statistics

Standard deviation2.1359524
Coefficient of variation (CV)0.059945013
Kurtosis-1.1177598
Mean35.631861
Median Absolute Deviation (MAD)1.23
Skewness0.465953
Sum735441.62
Variance4.5622926
MonotonicityNot monotonic
2024-09-22T17:54:41.106825image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.06 244
 
1.2%
34.05 236
 
1.1%
34.08 234
 
1.1%
34.07 231
 
1.1%
34.04 221
 
1.1%
34.09 212
 
1.0%
34.02 208
 
1.0%
34.1 203
 
1.0%
34.03 193
 
0.9%
33.93 181
 
0.9%
Other values (852) 18477
89.5%
ValueCountFrequency (%)
32.54 1
 
< 0.1%
32.55 3
 
< 0.1%
32.56 10
 
< 0.1%
32.57 18
0.1%
32.58 26
0.1%
32.59 11
0.1%
32.6 9
 
< 0.1%
32.61 14
0.1%
32.62 13
0.1%
32.63 18
0.1%
ValueCountFrequency (%)
41.95 2
< 0.1%
41.92 1
 
< 0.1%
41.88 1
 
< 0.1%
41.86 3
< 0.1%
41.84 1
 
< 0.1%
41.82 1
 
< 0.1%
41.81 2
< 0.1%
41.8 3
< 0.1%
41.79 1
 
< 0.1%
41.78 3
< 0.1%

Longitude
Real number (ℝ)

HIGH CORRELATION 

Distinct844
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-119.5697
Minimum-124.35
Maximum-114.31
Zeros0
Zeros (%)0.0%
Negative20640
Negative (%)100.0%
Memory size161.4 KiB
2024-09-22T17:54:41.295348image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-124.35
5-th percentile-122.47
Q1-121.8
median-118.49
Q3-118.01
95-th percentile-117.08
Maximum-114.31
Range10.04
Interquartile range (IQR)3.79

Descriptive statistics

Standard deviation2.0035317
Coefficient of variation (CV)-0.016756182
Kurtosis-1.3301524
Mean-119.5697
Median Absolute Deviation (MAD)1.28
Skewness-0.29780121
Sum-2467918.7
Variance4.0141394
MonotonicityNot monotonic
2024-09-22T17:54:41.600189image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-118.31 162
 
0.8%
-118.3 160
 
0.8%
-118.29 148
 
0.7%
-118.27 144
 
0.7%
-118.32 142
 
0.7%
-118.28 141
 
0.7%
-118.35 140
 
0.7%
-118.36 138
 
0.7%
-118.19 135
 
0.7%
-118.37 128
 
0.6%
Other values (834) 19202
93.0%
ValueCountFrequency (%)
-124.35 1
 
< 0.1%
-124.3 2
 
< 0.1%
-124.27 1
 
< 0.1%
-124.26 1
 
< 0.1%
-124.25 1
 
< 0.1%
-124.23 3
< 0.1%
-124.22 1
 
< 0.1%
-124.21 3
< 0.1%
-124.19 4
< 0.1%
-124.18 6
< 0.1%
ValueCountFrequency (%)
-114.31 1
 
< 0.1%
-114.47 1
 
< 0.1%
-114.49 1
 
< 0.1%
-114.55 1
 
< 0.1%
-114.56 1
 
< 0.1%
-114.57 3
< 0.1%
-114.58 2
< 0.1%
-114.59 2
< 0.1%
-114.6 3
< 0.1%
-114.61 3
< 0.1%

MedHouseVal
Real number (ℝ)

HIGH CORRELATION 

Distinct3842
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0685582
Minimum0.14999
Maximum5.00001
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size161.4 KiB
2024-09-22T17:54:41.766561image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0.14999
5-th percentile0.662
Q11.196
median1.797
Q32.64725
95-th percentile4.8981
Maximum5.00001
Range4.85002
Interquartile range (IQR)1.45125

Descriptive statistics

Standard deviation1.1539562
Coefficient of variation (CV)0.55785531
Kurtosis0.32787024
Mean2.0685582
Median Absolute Deviation (MAD)0.684
Skewness0.97776327
Sum42695.041
Variance1.3316148
MonotonicityNot monotonic
2024-09-22T17:54:41.955132image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.00001 965
 
4.7%
1.375 122
 
0.6%
1.625 117
 
0.6%
1.125 103
 
0.5%
1.875 93
 
0.5%
2.25 92
 
0.4%
3.5 79
 
0.4%
0.875 78
 
0.4%
2.75 65
 
0.3%
1.5 64
 
0.3%
Other values (3832) 18862
91.4%
ValueCountFrequency (%)
0.14999 4
< 0.1%
0.175 1
 
< 0.1%
0.225 4
< 0.1%
0.25 1
 
< 0.1%
0.266 1
 
< 0.1%
0.269 1
 
< 0.1%
0.275 1
 
< 0.1%
0.283 1
 
< 0.1%
0.3 2
< 0.1%
0.325 4
< 0.1%
ValueCountFrequency (%)
5.00001 965
4.7%
5 27
 
0.1%
4.991 1
 
< 0.1%
4.99 1
 
< 0.1%
4.988 1
 
< 0.1%
4.987 1
 
< 0.1%
4.986 1
 
< 0.1%
4.984 1
 
< 0.1%
4.976 1
 
< 0.1%
4.974 1
 
< 0.1%

Interactions

2024-09-22T17:54:36.891996image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:27.325911image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:28.610004image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:29.800357image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:30.975139image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:32.154607image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:33.462630image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:34.633621image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:35.730023image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:37.024590image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:27.456085image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:28.765221image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:29.934112image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:31.111621image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:32.291646image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:33.591401image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:34.758091image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:35.866647image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:37.148638image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:27.584039image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:28.892507image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:30.059061image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:31.237150image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:32.417310image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:33.725358image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:34.875870image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:35.989125image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:37.279543image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:27.836061image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:29.024387image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:30.193966image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:31.378529image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:32.556368image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:33.855879image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:35.003792image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:36.119443image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:37.412311image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:27.969272image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:29.153960image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:30.328907image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:31.508907image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:32.689192image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:33.996993image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:35.126341image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:36.260722image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:37.543591image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:28.106859image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:29.285831image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:30.473171image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:31.647638image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:32.824677image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:34.134789image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:35.262445image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:36.399314image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:37.679303image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:28.241324image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:29.440590image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:30.600934image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:31.772529image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:33.082693image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:34.259816image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:35.376040image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:36.530473image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:37.793364image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:28.355387image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:29.559186image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:30.716401image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:31.889985image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:33.206539image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:34.378837image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:35.498235image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:36.646874image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:37.920385image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:28.488912image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:29.678121image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:30.841616image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:32.024201image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:33.334187image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:34.510789image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:35.615202image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-22T17:54:36.765495image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-09-22T17:54:42.080822image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
AveBedrmsAveOccupAveRoomsHouseAgeLatitudeLongitudeMedHouseValMedIncPopulation
AveBedrms1.000-0.1320.082-0.1210.0470.011-0.125-0.2520.027
AveOccup-0.1321.0000.019-0.025-0.1510.181-0.257-0.0440.242
AveRooms0.0820.0191.000-0.2310.127-0.0450.2630.644-0.105
HouseAge-0.121-0.025-0.2311.0000.032-0.1510.075-0.147-0.284
Latitude0.047-0.1510.1270.0321.000-0.879-0.166-0.088-0.124
Longitude0.0110.181-0.045-0.151-0.8791.000-0.070-0.0100.124
MedHouseVal-0.125-0.2570.2630.075-0.166-0.0701.0000.6770.004
MedInc-0.252-0.0440.644-0.147-0.088-0.0100.6771.0000.006
Population0.0270.242-0.105-0.284-0.1240.1240.0040.0061.000

Missing values

2024-09-22T17:54:38.080981image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-09-22T17:54:38.294930image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

MedIncHouseAgeAveRoomsAveBedrmsPopulationAveOccupLatitudeLongitudeMedHouseVal
08.325241.06.9841271.023810322.02.55555637.88-122.234.526
18.301421.06.2381370.9718802401.02.10984237.86-122.223.585
27.257452.08.2881361.073446496.02.80226037.85-122.243.521
35.643152.05.8173521.073059558.02.54794537.85-122.253.413
43.846252.06.2818531.081081565.02.18146737.85-122.253.422
54.036852.04.7616581.103627413.02.13989637.85-122.252.697
63.659152.04.9319070.9513621094.02.12840537.84-122.252.992
73.120052.04.7975271.0618241157.01.78825337.84-122.252.414
82.080442.04.2941181.1176471206.02.02689137.84-122.262.267
93.691252.04.9705880.9901961551.02.17226937.84-122.252.611
MedIncHouseAgeAveRoomsAveBedrmsPopulationAveOccupLatitudeLongitudeMedHouseVal
206303.567311.05.9325841.1348311257.02.82471939.29-121.321.120
206313.517915.06.1458331.1412041200.02.77777839.33-121.401.072
206323.125015.06.0233771.0805191047.02.71948139.26-121.451.156
206332.549527.05.4450261.0785341082.02.83246139.19-121.530.983
206343.712528.06.7790701.1482561041.03.02616339.27-121.561.168
206351.560325.05.0454551.133333845.02.56060639.48-121.090.781
206362.556818.06.1140351.315789356.03.12280739.49-121.210.771
206371.700017.05.2055431.1200921007.02.32563539.43-121.220.923
206381.867218.05.3295131.171920741.02.12320939.43-121.320.847
206392.388616.05.2547171.1622641387.02.61698139.37-121.240.894